Inference
Streaming
Delivering model output token-by-token as it is generated rather than waiting for the full response.
In depth
Delivering model output token-by-token as it is generated rather than waiting for the full response. Streaming improves perceived latency in chat interfaces and coding agents. The Vercel AI SDK and most provider SDKs support streaming responses out of the box.
Example
In practice, developers reach for Streaming when they need the capability described above as part of an AI feature or workflow.
Go deeper at Developers Digest
Hands-on guides, comparisons, and tutorials that cover Inference.
FAQ
Common questions
What is Streaming?
Delivering model output token-by-token as it is generated rather than waiting for the full response.
Why does Streaming matter for AI developers?
Streaming sits in the Inference part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Where can I learn more about Streaming?
Developers Digest publishes tutorials and videos that cover Inference topics including Streaming. Check the blog and YouTube channel for hands-on walkthroughs.
Related
Related terms
Inference
Speculative Decoding
An inference technique where a small, fast draft model proposes several tokens ahead and the large target model checks them all in one parallel forward pass.
Inference
State Space Models (SSM)
State space models are sequence models that carry a fixed-size hidden state forward through the input, updating it with learned linear equations, rather than comparing every token to every other token like attention.
Inference
Decode Phase
The second phase of LLM inference, where the model generates output tokens one at a time, each step reading the KV cache built so far and adding to it.
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